Pydantic Collections

0.6.0 · active · verified Mon Apr 13

Pydantic-collections provides the `BaseCollectionModel` class, which allows for the manipulation and validation of collections of Pydantic models. It supports various Pydantic-compatible types within its collections. The library is actively maintained, with releases often corresponding to updates in the Pydantic ecosystem, and the current version is 0.6.0.

Warnings

breaking Version `0.5.0` of `pydantic-collections` introduced support for Pydantic V2. Projects upgrading Pydantic from V1 to V2 must also upgrade `pydantic-collections` to `v0.5.0` or newer. This also implies adapting to Pydantic V2's own breaking changes, such as method renames (`.dict()` to `.model_dump()`, `.json()` to `.model_dump_json()`) and configuration changes (e.g., `Config` inner class to `model_config` attribute).
Fix: Upgrade `pydantic-collections` to `0.5.0+` when migrating to Pydantic V2. Review Pydantic's official migration guide for V1 to V2 changes and update method calls and configurations accordingly.
gotcha By default, `BaseCollectionModel` enforces strict assignment validation. Attempting to append or assign raw dictionaries or objects that are not already instances of the collection's base model will raise a `ValidationError`.
Fix: Ensure that items assigned to or appended to a `BaseCollectionModel` instance are pre-validated instances of the expected Pydantic model. If non-strict behavior is desired, consult the library's documentation on how to configure this (e.g., via Pydantic model config).
gotcha The `pydantic-collections` library declares a dependency on `pydantic>=1.8.2,<3.0`. Be cautious when pinning `pydantic` in your project, especially to `<2`, as this can cause conflicts with `pydantic-collections` versions expecting V2 features or if `pydantic-collections` itself updates to explicitly require Pydantic V2+ in a future major version.
Fix: Avoid overly restrictive `pydantic` version pinning. If you need to use Pydantic V1 features with a V2-compatible `pydantic-collections` version, import from `pydantic.v1` where necessary (available in Pydantic >=1.10.17).

Install

pip install pydantic-collections Install latest version

Imports

BaseCollectionModel
```
from pydantic_collections import BaseCollectionModel
```
The primary class for creating Pydantic-validated collections.

Quickstart

This example demonstrates defining a Pydantic model (`User`) and then using `BaseCollectionModel` to create a validated collection of `User` objects. It shows instantiation and serialization for Pydantic V2.

from datetime import datetime
from pydantic import BaseModel
from pydantic_collections import BaseCollectionModel

class User(BaseModel):
    id: int
    name: str
    birth_date: datetime

class UserCollection(BaseCollectionModel[User]):
    pass

user_data = [
    {'id': 1, 'name': 'Bender', 'birth_date': '2010-04-01T12:59:59'},
    {'id': 2, 'name': 'Balaganov', 'birth_date': '2020-04-01T12:59:59'},
]
users = UserCollection(user_data)

print(users)
# For Pydantic v2.x, use model_dump() and model_dump_json()
print(users.model_dump())
print(users.model_dump_json())

view raw JSON →